• 한국전자거래학회지
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• 제7권1호
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• pp.141-152
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• 2002

Data dictionary is a collection of meta-data, which describes data produced and consumed while performing business processes. Data dictionary is an essential element for business process standardization and automation, and has a fundamental role in ERP application management and customization. Also, data dictionary facilitates B2B processes by enabling painless integration of business processes between various enterprises. We implemented data dictionary support in SEA＋, a component- based scalable ERP system developed in ETRI, and found out that it's a plausible feature of business information system. We discovered that data dictionary promotes semantic, not syntactic, data management, which can make it possible to leverage viability of the tool in the coming age of more meta-data oriented computing world. We envision that business data dictionary is a firm foundation of adapting business knowledge, applications and processes into the semantic web based enterprise infra-structure.

• 한국전자거래학회:학술대회논문집
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• 한국전자거래학회 2001년도 International Conference CALS/EC KOREA
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• pp.483-491
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• 2001

Data dictionary is a collection of metadata about data defined, produced and consumed while performing business processes. Data dictionary is an essential element for business process standardization and automation. Data dictionary also has a fundamental role in ERP application management and customization. Finally, data dictionary helps B2B by gracefully integrating intra-enterprise business processes and inter-enterprise business processes. This paper gives some clues about the importance of data dictionary in ERP and B2B, and introduces data dictionary support of SEA+, a component-based scalable ERP package system.

• 한국전자거래학회지
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• 제8권3호
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• pp.37-52
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• 2003

PLIB으로 알려진 ISO 13584 부품 라이브러리 국제 표준은 상품의 분류와 각 상품 분류별 특성을 묘사하는 기준으로서 전자 상거래 분야로 그 응용영 역을 넓혀 나가고 있다. PLIB 표준은 여러 권으로 구성된 표준인데, 그 중 파트 42는 전자 카탈로그 또는 부품 라이브러리의 데이터 사전 (Data Dictionary)를 작성하는데 정보모델 (Information Model)과 설계원칙 (Design Principles)을 제공한다. PLIB 파트42의 정보모델을 기반으로 작성된 데이터 사전을 이용하여 전자 카탈로그 시스템을 구축하면, 향후 산업별, 부품대상별로 구축될 다양한 전자 카탈로그 시스템간의 통합 (Integration)과 상호운용 (Interoperation)을 쉽게 달성할 수 있다. 본 연구는 우선, 전자 카탈로그 또는 부품 라이브러리에서 데이터 사전의 역할과 요구 사항을 정리하고, PLIB 파트 42의 내용을 분석한다. 그리고 분석 결과를 바탕으로 금형부품 데이터 사전을 작성하고 이를 이용하여 기업간 전자 상거래 (B2B e-Commerce)용 전자 카탈로그 시스템을 구축한 결과를 정리한다.

• 정보처리학회논문지D
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• 제8D권5호
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• pp.587-592
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• 2001

사무자동화의 필요성이 증가함에 따라 많은 응용 프로그램이 개발되고 있으며, 전자사전은 이러한 사무용 프로그램의 주요 구성요소 중 하나이다. 효율적인 전자사전은 빠른 검색을 지원해야 하며, 타 사전과 데이터 교환을 통해 사어 및 신조어에 대처할 수 있어야 한다. 또한 전자 사전 프로그램 자체의 재사용의 고려하여 전자 사전 프로그램 구축비용 및 시간을 절감할 수 있어야 한다. 본 논문에서는 사전 내부 데이터 표현 형식을 정의하여 정의된 표현 방식에 기초한 타 전자 사전 데이터 교환을 가능하게 하는 방안을 제시하였다. 또한 재사용 및 호환성을 향상시키기 위하여 사전 구조를 시스템 사전 컴포넌트와 사용자 사전 컴포넌트로 나누어 구현하여 차후 바이너리 단위로의 재사용을 가능하게 하였다. 컴포넌트화로 인한 검색속도 저하 가능성은 트라이 및 B 트리 인덱스 구조를 통하여 효과적으로 방지하였다.

• International Journal of Contents
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• 제17권4호
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• pp.1-15
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• 2021

Named entity recognition (NER) is a crucial task for NLP, which aims to extract information from texts. To build NER systems, deep learning (DL) models are learned with dictionary features by mapping each word in the dataset to dictionary features and generating a unique index. However, this technique might generate noisy labels, which pose significant challenges for the NER task. In this paper, we proposed DL-dictionary features, and evaluated them on two datasets, including the OntoNotes 5.0 dataset and our new infectious disease outbreak dataset named GFID. We used (1) a Bidirectional Long Short-Term Memory (BiLSTM) character and (2) pre-trained embedding to concatenate with (3) our proposed features, named the Convolutional Neural Network (CNN), BiLSTM, and self-attention dictionaries, respectively. The combined features (1-3) were fed through BiLSTM - Conditional Random Field (CRF) to predict named entity classes as outputs. We compared these outputs with other predictions of the BiLSTM character, pre-trained embedding, and dictionary features from previous research, which used the exact matching and partial matching dictionary technique. The findings showed that the model employing our dictionary features outperformed other models that used existing dictionary features. We also computed the F1 score with the GFID dataset to apply this technique to extract medical or healthcare information.

• 센서학회지
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• 제32권6호
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• pp.481-486
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• 2023

Anomaly detection holds paramount significance across diverse fields, encompassing fraud detection, risk mitigation, and sensor evaluation tests. Its pertinence extends notably to the military, particularly within the Warrior Platform, a comprehensive combat equipment system with wearable sensors. Hence, we propose a data-compression-based anomaly detection approach tailored to unlabeled time series and sequence data. This method entailed the construction of two distinctive features, typicality and atypicality, to discern anomalies effectively. The typicality of a test sequence was determined by evaluating the compression efficacy achieved through the pattern dictionary. This dictionary was established based on the frequency of all patterns identified in a training sequence generated for each sensor within Warrior Platform. The resulting typicality served as an anomaly score, facilitating the identification of anomalous data using a predetermined threshold. To improve the performance of the pattern dictionary method, we leveraged atypicality to discern sequences that could undergo compression independently without relying on the pattern dictionary. Consequently, our refined approach integrated both typicality and atypicality, augmenting the effectiveness of the pattern dictionary method. Our proposed method exhibited heightened capability in detecting a spectrum of unpredictable anomalies, fortifying the stability of wearable sensors prevalent in military equipment, including the Army TIGER 4.0 system.

• 한국컴퓨터정보학회논문지
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• 제18권9호
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• pp.101-109
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• 2013

데이터 품질 관리는 매우 중요하다. 본 연구는 효율적인 기업 데이터의 품질 관리를 위한 데이터 표준화 설계를 유통 상품 사례로 구축 방안을 제시하고 그 효과를 검증 하였다. 데이터 표준화 설계 방안으로 데이터 표준화 체계와 데이터 사전을 설계 하였다. 데이터 표준화 체계 설계를 위하여 데이터를 분류, 속성, 식별하였으며, 데이터 사전 설계를 위하여 데이터 사전 설계 프로세스와 단어 용어 도메인 코드사전을 구축하고, 데이터 표준화 설계 방안을 제시하였다. 제시한 데이터 표준화 방안의 효율성을 정량적, 정성적 방법으로 검증한 결과데이터표준화로 인한 데이터 품질은 24% 및 데이터 사전의 속성 설계인 일관성에 대한 데이터의 구조적 품질은 7% 향상되고, 유효함을 입증하였다.

• 한국전자거래학회지
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• 제6권2호
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• pp.127-142
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• 2001

For the B2B e-commerce and SCM (Supply Chain Management), standardization of electronic catalogue that contains product and business data is important. Especially, standardization of hierarchies that is required for categorization, and standardization of product properties are difficult and costly to maintain. The ability of searching for items and data in databases is critical for successful e-commerce system. This paper introduces the data dictionary of PUB (ISO 13584) part 42 which can establish the standard of product data. The method is applied to develop the data dictionary of automotive parts.

• Smart Structures and Systems
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• 제25권2호
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• pp.123-133
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• 2020

Compressive sensing (CS) is a newly developed data acquisition and processing technique that takes advantage of the sparse structure in signals. Normally signals in their primitive space or format are reconstructed from their compressed measurements for further treatments, such as modal analysis for vibration data. This approach causes problems such as leakage, loss of fidelity, etc., and the computation of reconstruction itself is costly as well. Therefore, it is appealing to directly work on the compressed data without prior reconstruction of the original data. In this paper, a direct approach for modal analysis of damped systems is proposed by decomposing the compressed measurements with an appropriate dictionary. The damped free vibration function is adopted to form atoms in the dictionary for the following sparse decomposition. Compared with the normally used Fourier bases, the damped free vibration function spans a space with both the frequency and damping as the control variables. In order to efficiently search the enormous two-dimension dictionary with frequency and damping as variables, a two-step strategy is implemented combined with the Orthogonal Matching Pursuit (OMP) to determine the optimal atom in the dictionary, which greatly reduces the computation of the sparse decomposition. The performance of the proposed method is demonstrated by a numerical and an experimental example, and advantages of the method are revealed by comparison with another such kind method using POD technique.

• 음성과학
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• 제8권1호
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• pp.33-52
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• 2001

A bilingual sound dictionary in Korean and English has been created for a broad range of sound reference to cross-linguistic, dialectal, native language (L1)-transferred biological and allophonic variations. The paper demonstrates that the pronunciation dictionary of the lexicon is inadequate for sound reference due to the preponderance of unmarked sounds. The audio registry consists of the three-way comparison of 1) English speech from native English speakers, 2) Korean speech from Korean speakers, and 3) English speech from Korean speakers. Several sub-dictionaries have been created as the foundation research for independent development. They are 1) a pronunciation dictionary of the Korean lexicon in a keyboard-compatible phonetic transcription, 2) a sound dictionary of L1-interfered language, and 3) an audible dictionary of Korean sounds. The dictionary was designed to facilitate the exchange of the speech signal and its corresponding text data on various media particularly on CD-ROM. The methodology and findings of the construction are discussed.